Image Classification
Transformers
Safetensors
mobilevit
knowledge_distillation
vision
Generated from Trainer
Instructions to use c14kevincardenas/mobilevit-small_alpha0.7_temp3.0_t3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use c14kevincardenas/mobilevit-small_alpha0.7_temp3.0_t3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="c14kevincardenas/mobilevit-small_alpha0.7_temp3.0_t3") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("c14kevincardenas/mobilevit-small_alpha0.7_temp3.0_t3") model = AutoModelForImageClassification.from_pretrained("c14kevincardenas/mobilevit-small_alpha0.7_temp3.0_t3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 462db587894d8e5ffe3c44aeb55420437edc74e01617ff0e900d3db1b2d5570e
- Size of remote file:
- 5.18 kB
- SHA256:
- 30924c20a38e23ab490769a0f5fa19c95ae2a255f1de546ce3217aaab284a08f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.